AI products that solve a real task, not a demo
Adding a language model to an app is easy; building an AI product people rely on is not. Answers need to be useful, fast and safe, costs need to stay predictable and the interface has to make the AI feel helpful rather than unpredictable. Our team has shipped AI in our own App Store apps, from a Turkish-language chatbot to AI fitness plans and document scanning with OCR, and we bring that product experience to client AI products.
Challenges we solve
Quality and trust
Models can be wrong with confidence. Products need guardrails, checks and an interface that sets the right expectations.
Running costs
Every request costs money. Without limits, caching and the right model choice, a successful launch can become unprofitable.
Differentiation
A thin wrapper around a public model is easy to copy. Lasting products add proprietary data, workflow or a specific audience.
Language and locale
Quality outside English varies, and users notice unnatural phrasing immediately in their own language.
What we build
AI assistants and chat
Conversational interfaces with streaming responses, conversation history, image input and safe handling of user content.
Personalised generation
Plans, recommendations and content generated from structured user data, validated before they reach the screen.
Document and image AI
Scanning, OCR, extraction and summarisation that turn photos and PDFs into usable, searchable information.
Retrieval over your data
Answers grounded in your documents or catalogue, with sources shown so users can verify them.
Usage limits and monetisation
Credits, tiers and subscriptions linked to model usage, so revenue grows with cost.
Built by our team
AI products we run ourselves: a chatbot for Turkish speakers, an AI fitness coach and AI document scanning with OCR.
Questions
Which AI model should our product use?
It depends on the task, language, speed and budget. We usually test two or three models on your real examples and choose the one with the best quality for the cost, while keeping it easy to switch later.
Can AI features run on the device instead of the cloud?
Some can. OCR, image classification and smaller models can run on-device for speed and privacy. Larger language tasks still usually need a cloud model. We combine both where it makes sense.
How do you stop the AI from giving harmful or wrong answers?
We restrict what the model is asked to do, validate structured outputs, add moderation on inputs and outputs and design the interface so users can correct or report results.
Can you build an AI app for a non-English market?
Yes. Our Genius chatbot serves Turkish speakers, and we test prompts and responses in each target language rather than translating English prompts and hoping for the best.
Have a project in mind?
Tell us about it. Our team in Istanbul replies within one business day with next steps and a free intro call.
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